code: def _verify_output_shape(
      acqf: Any, X: Tensor, output: Tensor
  ) -> bool:
      r"""
      Performs the output shape checks for `t_batch_mode_transform`. Output shape checks
      help in catching the errors due to AcquisitionFunction arguments with erroneous
      return shapes before these errors propagate further down the line.
  
      This method checks that the `output` shape matches either the t-batch shape of X
      or the `batch_shape` of `acqf.model`.
  
      Args:
          acqf: The AcquisitionFunction object being evaluated.
          X: The `... x q x d`-dim input tensor with an explicit t-batch.
          output: The return value of `acqf.method(X, ...)`.
  
      Returns:
          True if `output` has the correct shape, False otherwise.
      """
      try:
          X_batch_shape = X.shape[:-2]
          if output.shape == X_batch_shape:
              return True
          if (
              output.shape == torch.Size()
              and X_batch_shape == torch.Size([1])
          ):
              # X has a batch shape of [1] which gets squeezed.
              return True
          # Cases with model batch shape involved.
          model_b_shape = acqf.model.batch_shape
          if output.shape == model_b_shape:
              # Simple inputs with batched model.
              return True
          model_b_dim = len(model_b_shape)
          if output.shape == X_batch_shape[
              :-model_b_dim
          ] + model_b_shape and all(
              xs in [1, ms]
              for xs, ms in zip(
                  X_batch_shape[-model_b_dim:], model_b_shape
              )
          ):
              # X has additional batch dimensions beyond the model batch shape.
              # For a batched model, some of the input dimensions might get broadcasted
              # to the model batch shape. In that case the acquisition function output
              # should replace the right-most batch dim of X with the model's batch shape.
              return True
          return False
      except (AttributeError, NotImplementedError):
          # acqf does not have model or acqf.model does not define `batch_shape`
          warnings.warn(
              "Output shape checks failed! Expected output shape to match t-batch shape"
              f"of X, but got output with shape {output.shape} for X with shape"
              f"{X.shape}. Make sure that this is the intended behavior!",
              RuntimeWarning,
          )
          return True
  
file_path: botorch/botorch/utils/transforms.py
imports: from __future__ import annotations
  import warnings
  from functools import wraps
  from typing import Any, Callable, List, Optional, TYPE_CHECKING
  import torch
  from botorch.utils.safe_math import logmeanexp
  from torch import Tensor
label_desc: Use image node_id 5 for calling a global function with example usage: _verify_output_shape(acqf, X, output) and returns: False, True, True, True, True, True